18 citations · 28 across the 8 of their papers we have counts for
5 papers · 1 filter
JudgeBoard: Benchmarking and Enhancing Small Language Models for Reasoning Evaluation
Zhenyu Bi, Gaurav Srivastava, Yang Li +4
While small language models (SLMs) have shown promise on various reasoning tasks, their ability to judge the correctness of answers remains unclear compared to large language model…
OPTAGENT: Optimizing Multi-Agent LLM Interactions Through Verbal Reinforcement Learning for Enhanced Reasoning
Zhenyu Bi, Meng Lu, Yang Li +4
Large Language Models (LLMs) have shown remarkable reasoning capabilities in mathematical and scientific tasks. To enhance complex reasoning, multi-agent systems have been proposed…
Bridging Literature and the Universe Via A Multi-Agent Large Language Model System
Xiaowen Zhang, Zhenyu Bi, Patrick Lachance +3
As cosmological simulations and their associated software become increasingly complex, physicists face the challenge of searching through vast amounts of literature and user manual…
DEBATE, TRAIN, EVOLVE: Self Evolution of Language Model Reasoning
Gaurav Srivastava, Zhenyu Bi, Meng Lu +1
Large language models (LLMs) have improved significantly in their reasoning through extensive training on massive datasets. However, relying solely on additional data for improveme…
Population Aware Diffusion for Time Series Generation
Yang Li, Han Meng, Zhenyu Bi +2
Diffusion models have shown promising ability in generating high-quality time series (TS) data. Despite the initial success, existing works mostly focus on the authenticity of data…